University of Houston scientists learn that rare bacterium ‘plays dead’ to survive
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Updates every hour. Last Updated: 6-Nov-2025 01:12 ET (6-Nov-2025 06:12 GMT/UTC)
On Mars, dust devils and winds reach speeds of up to 160 km/h and are therefore faster than previously assumed: This shows a study by an international research team led by the University of Bern. The researchers analyzed images taken by the Bernese Mars camera CaSSIS and the stereo camera HRSC with the help of machine learning. The study provides a valuable data basis for a better understanding of atmospheric dynamics, which is important for better climate models and future Mars missions.
Combing through 20 years of images from the European Space Agency’s Mars Express and ExoMars Trace Gas Orbiter spacecraft, scientists have tracked 1039 tornado-like whirlwinds to reveal how dust is lifted into the air and swept around Mars’s surface.
Published today in Science Advances, their findings – including that the strongest winds on Mars blow much faster than we thought – give us a much clearer picture of the Red Planet’s weather and climate.
And with these ‘dust devils’ collected into a single public catalogue, this research is just the beginning. Besides pure science, it will be useful for planning future missions, for example incorporating provisions for the irksome dust that settles on the solar panels of our robotic rovers.
New analyses of the largest impact crater on the moon reveal unexpected insights into its tumultuous past. They also suggest that once astronauts return to the moon, they will have access to a veritable gold mine of scientific clues that may help scientists solve some of the longstanding mysteries of how the moon came to be.
According to theory, massive red supergiant stars should cause most supernovae, yet they are rarely observed. New James Webb Space Telescope (JWST) observations indicate these supernovae likely can occur but are hidden in dust. Star’s dust was unusually carbon-rich, suggesting atypical chemical mixing during its death throes. Study marks first time JWST identified a supernova’s source star and first time supernova was imaged in mid-infrared wavelengths.
A new study co-led by the University of Oxford and Google Cloud has shown how general-purpose AI can accurately classify real changes in the night sky — such as an exploding star, a black hole tearing apart a passing star, a fast-moving asteroid, or a brief stellar flare from a compact star system — and explain its reasoning, without the need for complex training.